Does Keystroke Dynamics tell us about Emotions? A Systematic Literature Review and Dataset Construction

There is strong evidence that emotional states affect the Human's performance and decision-making. Therefore, understanding Human emotions has become of great concern in the field of Human-Computer Interaction (HCI). One way to an online emotion recognition is through keystroke dynamics. Keystr...

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Bibliographic Details
Main Authors: Maalej, Aicha, Kallel, Ilhem
Format: Conference Proceeding
Language:English
Subjects:
data collection
Emotion recognition
Feature extraction
HCI
Keyboards
keystroke dynamics
Physiology
Protocols
Rhythm
Systematic Literature Review (SLR)
Systematics
web application
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Summary:There is strong evidence that emotional states affect the Human's performance and decision-making. Therefore, understanding Human emotions has become of great concern in the field of Human-Computer Interaction (HCI). One way to an online emotion recognition is through keystroke dynamics. Keystroke Dynamics focuses on the particular way a person types on a keyboard. To provide insight, assess recent works, and guide future researches in this field, a Systematic Literature Review (SLR) is conducted. An SLR adopts a rigorous procedure with the definition of a formal review protocol.The primary aim of this paper is to highlight the effectiveness of using keystroke dynamics biometrics in recognizing emotions by systematically presenting research efforts in the past decade. We provide insight into such an approach by summarizing and discussing the data acquisition procedures, datasets, extracted features, classification methods, and performance measures used in previous researches.In light of these findings and the noticed scarcity of datasets related to emotion recognition through keystroke dynamics, we develop and host an interactive web application to construct a new dataset. The findings of this work reveal new interesting research directions and may motivate the research community to develop automatic emotion recognition systems based on keystroke dynamics.
ISSN:2472-7571
DOI:10.1109/IE49459.2020.9155004